This paper considers an OFDMA-based cooperative cognitive radio network where the secondary users (SUs) act as the relay of the primary users (PUs) while guaranteeing the quality of service (QoS) of the PUs. In return...
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Smart grid, a concept proposed in 2003, is now attracting more and more attention because of its ability to integrate intensive information and renewable energy generating infrastructures. This paper focuses on schedu...
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ISBN:
(纸本)9781479947249
Smart grid, a concept proposed in 2003, is now attracting more and more attention because of its ability to integrate intensive information and renewable energy generating infrastructures. This paper focuses on scheduling charging process between multiple electric vehicles and charging stations in smart grid with renewable energy and storage devices. From the perspective of the whole system, the goal of minimizing the time average electricity cost with time-varying electricity price can be reached in this paper. With the participation of storage devices, charging-station-private renewable generation and electric vehicles power demands, we mathematically formulate a stochastic optimal problem and address it by employing Lyapunov optimization methods. Through mathematical derivation, stability of storage devices is achieved. Meanwhile, the upper bound for time average electricity cost can be calculated. The feature of our research is the independence on stochastic distribution of demand and renewable generation. Simulation results show the convergence of storage device state of charging（SOC） and illustrate the efficiency and performance of our algorithm.
Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the proces...
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ISBN:
(纸本)9781479947249
Point matching is an important component of image *** years,Coherent Point Drift(CPD) method becomes a very popular point matching *** treats point matching as a probability estimation problem and speeds up the process of matching a *** this method,one set of points are thought to be sampled from a Gaussian Mixture Model(GMM),which is centered by the other set of ***,CPD is sensitive to outliers and noises,especially when the noise ratio increased or the number of outliers gets much *** deal with this problem,we introduce shape context into the step of searching for matching points and then improve the form of prior probabilities of GMM in this *** main idea of our method is that if the most points in a data set are likely to be matched to a particular centroid,this Gaussian component should be have a more influence to ***,we set prior probability of GMM with the similarity between GMM components and the data *** the computation of similarity is based on shape *** experiments on 2D and 3D images show that when noise ratio is low,our method performs as well as CPD does,but as the ratio increased,our method is more robust and satisfactory than CPD.
Furnace exit gas temperature(FEGT) is the key parameter in the furnace ash fouling monitoring system. Since the standard least squares support vector machine(LSSVM) is not suitable for online identification and contro...
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ISBN:
(纸本)9781479947249
Furnace exit gas temperature(FEGT) is the key parameter in the furnace ash fouling monitoring system. Since the standard least squares support vector machine(LSSVM) is not suitable for online identification and control of FEGT,a novel CM-LSSVM-PLS method is proposed to predict FEGT in this paper. In the process of CM-LSSVM-PLS method, c-means cluster(CM) algorithm is used to partition the training data into several different subsets by considering the characteristics of operational data. Submodels are subsequently developed in the individual subsets based on LSSVM method. Partial least squares algorithm(PLS) is employed as the combination strategy. The online updating algorithm is then applied to the CM-LSSVM-PLS model. The proposed online model is verified through operation data of a 300 MW generating unit. The simulation results show that the proposed online updating model is effective for online FEGT forecasting.
This paper mainly discusses the remote tracking problem with partly quantized information and packet-dropout. Since the network exists between the remote plant and the local plant, any information transmitted between ...
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ISBN:
(纸本)9781479947249
This paper mainly discusses the remote tracking problem with partly quantized information and packet-dropout. Since the network exists between the remote plant and the local plant, any information transmitted between each other will experience the quantization errors and may be lost. In this situation, the controller of the local system needs to consider both the exact local information and the inaccurate remote information. A state feedback controller is adopted and the theorems to design such controller are given in terms of bilinear matrix inequalities(BMIs). Moreover, an algorithm is proposed and these BMIs are converted into a convex optimization problem. Finally, the efficiency of the proposed method is demonstrated by a simulation example.
In this paper, we consider the robust fault tolerant control of the distributed networked controlsystems(DNCSs). In DNCSs, sub-systems are connected with each other through a communication network. Each sub-system ha...
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ISBN:
(纸本)9781479947249
In this paper, we consider the robust fault tolerant control of the distributed networked controlsystems(DNCSs). In DNCSs, sub-systems are connected with each other through a communication network. Each sub-system has its own sensor, controller, actuator and quantizer. The output of each sub-system will be transmitted to all other sub-systems through the network. As a result, quantization errors and packet-dropouts cannot be avoided. We also consider the actuator faults situations, including outage, loss of effectiveness and impulse which is modeled by a Markov chain in this paper. A mode-based static output feedback controller is proposed to stable the DNCSs and to meet the robust H-inf performance. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.
This paper studies the containment and group dispersion control for a multi-robot system in the presence of dynamic leaders. Each robot is represented by a doubleintegrator dynamic model and a distributed control algo...
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This paper studies the containment and group dispersion control for a multi-robot system in the presence of dynamic leaders. Each robot is represented by a doubleintegrator dynamic model and a distributed control algorithm is developed to drive the multi-robot system to follow a group of dynamic leaders with containment and group dispersion behaviors. The effectiveness of the algorithm is then verified on a multi-robot control platform.
High dimension of the features employed for face recognition is the main reason to slow down the recognition speed. Additionally, selecting salient facial features has significant impact on the efficiency of face reco...
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High dimension of the features employed for face recognition is the main reason to slow down the recognition speed. Additionally, selecting salient facial features has significant impact on the efficiency of face recognition. In order to get the sparse and salient facial features, this paper propose a new sparse learning approach for salient facial feature description. This approach is to learn the feature evaluation vector with the training samples composed of within- and between-class distance vector sets. Then, the feature evaluation vector is employed to construct a new model for salient facial feature description. Experimental results show that the proposed method achieves much better face recognition performance with lower feature dimensionality.
This paper is concerned with stochastic model predictive control for Markovian jump linear systems with additive disturbance, where the systems are subject to soft constraints on the system state and the disturbance s...
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